2. Digital Image Processing (DIP)
University of Kurdistan
Digital Image Processing (DIP)
Lecture1: An Introduction to DIP
Lecturer:
Kaveh Mollazade, Ph.D.
Department of Biosystems Engineering, Faculty of Agriculture, University of Kurdistan, Sanandaj, IRAN.

3. “One picture is worth more than ten thousand words ”
Introduction
“One picture is worth more than ten thousand words ”
Anonymous 1

4. This lecture will cover:
Contents
This lecture will cover:
What is a digital image?
What is digital image processing (DIP)?
History of digital image processing
Key stages in digital image processing
State of the art examples of digital image processing 2

5. What is a digital image?
A digital image is a representation of a two-dimensional image as a finite set of digital values, called picture elements or pixels. 3

6. What is a digital image? (cont…)
Pixel values typically represent gray levels, colors, heights, opacities, etc.
Remember digitization implies that a digital image is an approximation of a real scene.
1 pixel 4

7. What is a digital image? (cont…)
Common image formats include:
1 sample per point (B&W or Grayscale)
3 samples per point (Red, Green, and Blue)
4 samples per point (Red, Green, Blue, and “Alpha”, a.k.a. Opacity)
For most of this course we will focus on grey-scale images. 5

8. What is digital image processing (DIP)?
Digital image processing focuses on two major tasks:
Improvement of pictorial information for human interpretation.
Processing of image data for storage, transmission, and representation for autonomous machine perception.
Some argument about where image processing ends and fields such as image analysis and computer vision start. 6

9. In this course we will stop here
What is digital image processing (DIP)? (cont…)
The continuum from image processing to computer vision can be broken up into low-, mid- and high-level processes.
Low Level Process
Input: Image Output: Image
Examples: Noise removal, image sharpening
Mid Level Process
Input: Image Output: Attributes
Examples: Object recognition, segmentation
High Level Process
Input: Attributes Output: Understanding
Examples: Scene understanding, autonomous navigation
In this course we will stop here 7

10. Fundamental Steps in DIP8

11. Radiation from electromagnetic (EM) spectrum9

12. History of DIP
Early 1920s: One of the first applications of digital imaging was in the newspaper industry.
The Bartlane cable picture transmission service.
Images were transferred by submarine cable between London and New York.
Pictures were coded for cable transfer and reconstructed at the receiving end on a telegraph printer.
Early digital image 10

13. History of DIP (cont…)
Mid to late 1920s: Improvements to the Bartlane system resulted in higher quality images.
New reproduction processes based on photographic techniques.
Increased number of tones in reproduced images.
Early 15 tone digital image
Improved digital image 11

14. History of DIP (cont…)
1960s: Improvements in computing technology and the onset of the space race led to a surge of work in digital image processing.
1964: Computers used to improve the
quality of images of the moon taken by the Ranger 7 probe.
Such techniques were used in other
space missions including the Apollo
landings.
A picture of the moon taken by the Ranger 7 probe minutes before landing 12

15. History of DIP (cont…)
1970s: Digital image processing begins to be used in medical applications.
1979: Sir Godfrey N. Hounsfield & Prof.
Allan M. Cormack share the Nobel Prize
in medicine for the invention of tomography,
the technology behind Computerised Axial
Tomography (CAT) scans.
Typical head slice CAT
image 13

16. History of DIP (cont…)
1980s - Today: The use of digital image processing techniques has exploded and they are now used for all kinds of tasks in all kinds of areas.
Image enhancement/restoration
Medical visualisation
Industrial inspection
Law enforcement
Human computer interfaces (HCI) 14

17. Examples: Image Enhancement
One of the most common uses of DIP techniques: improve quality, remove noise, etc. 15

18. Examples: The Hubble Telescope
Launched in 1990 the Hubble telescope can take images of very distant objects. However, an incorrect mirror made many of Hubble’s images useless. Image processing techniques were used to fix this. 16

19. Original MRI Image of a Dog Heart
Examples: Medicine
Take slice from MRI scan of canine heart, and find boundaries between types of tissue.
Image with gray levels representing tissue density.
Use a suitable filter to highlight edges.
Original MRI Image of a Dog Heart
Edge Detection Image 17

20. Examples: GIS Geographic Information Systems (GIS)
Digital image processing techniques are used extensively to manipulate satellite imagery.
Terrain classification
Meteorology 18

21. Examples: Industrial Inspection
Human operators are expensive, slow, and unreliable.
Make machines do the job instead.
Industrial vision systems are used in all kinds of industries.
Can we trust them? 19

22. Examples: Law Enforcement
Image processing techniques are used extensively by law enforcers.
Number plate recognition for speed cameras/automated toll systems
Finger print recognition
Enhancement of CCTV images 20

23. Examples: HCI Try to make human computer interfaces more natural.
Face recognition
Gesture recognition
Does anyone remember the user interface from “Minority Report”?
These tasks can be extremely difficult. 21

24. Applications: Biosystems Engineering (BE)
Sorting and grading of fruits and vegetables 22

25. Applications: Biosystems Engineering (BE)
Plant diseases detection / Weed detection 23

26. Applications: Biosystems Engineering (BE)
Poultry / meat quality inspection 24

27. Applications: Biosystems Engineering (BE)
Food quality evaluation 25

28. Applications: Biosystems Engineering (BE)
Other examples …..
What do you think? 26

29. Next time we will start to see how it all works…
Summary
We have looked at:
What is a digital image?
What is digital image processing?
Key stages in digital image processing
History of digital image processing
State of the art examples of digital image processing
Next time we will start to see how it all works… 27